# Quantum-Aided Active Device Detection in Energy-Harvesting Symbiotic Radio Networks

arXiv: https://arxiv.org/abs/2609.26565 · HTML: https://mlsanity.com/paper/2609.26565/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 15 references that are in the map.
- First posted on arXiv 22 Sep 2026.

## Builds on (most cited first, 3 of 3)

- [Modulation and Coding for NOMA and RSMA](https://mlsanity.com/paper/2410.00239/) (2024)
- [Symbiotic Radio: Cognitive Backscattering Communications for Future Wireless Networks](https://mlsanity.com/paper/2007.01506/) (2020)
- [Quantum Annealing for Active User Detection in NOMA Systems](https://mlsanity.com/paper/2411.05411/) (2024)

## Abstract (arXiv)

Massive connectivity in next-generation networks demands energy- and spectrum-efficient solutions for large-scale Internet of Things (IoT) deployments. Symbiotic radio (SR) enables passive IoT devices to communicate by backscattering existing cellular transmissions. A key challenge in uplink SR is active device detection (ADD), which directly affects decoding reliability, interference management, and system throughput. We propose an energy-harvesting code-domain non-orthogonal multiple access (NOMA)-SR system in which IoT devices harvest energy from ambient uplink signals and backscatter information using low-density spreading (LDS) codes. To reduce the complexity of ADD, Grover's quantum search algorithm is employed, providing a quadratic reduction in oracle-query complexity over exhaustive maximum-likelihood (ML) search. Numerical results show that the proposed approach closely approaches ML performance while substantially reducing the number of search iterations, demonstrating its potential for scalable ambient IoT systems.